• Journal of Astronomy and Space Sciences
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• 제24권1호
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• pp.31-38
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• 2007

We have investigated the evolutionary status of 85 Peg within the framework of standard evolutionary theory. 85 Peg has been known to be a visual and spectroscopic binary system in the solar neighborhood. In spite of the accurate information of the total mass (${\sim}1.5M_{\odot}$) and the distance (${\sim}12pc$) from the HIPPARCOS parallax, it has been undetermined an individual mass, therefore the evolved status of the system. Moreover, the coupled uncertainties of chemical composition and age, make matters worse in predicting an evolutionary status of the system. Nevertheless, we computed the various possible models for 85 Peg, and then calibrated stellar parameters by adjusting to the recent observational data. Our modelling computation has included recently updated input physics and stellar theory such as opacity, equation of state, and chemical diffusion. Through a statistical assessment, we have derived a confident parameter set as the best solution which minimized $X^{2}$ within the observational error domain. Most of all, we found that 85 Peg is not a binary system but a triple system with an unseen companion 85 Peg $B_{b}\;{\sim}0.16M_{\odot}$. The aim of the present paper is (1) to provide a complete modelling of the stellar system based on the evolutionary theory, and (2) to constrain the physical dimensions such as mass, metallicity and age.

• Structural Engineering and Mechanics
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• 제21권5호
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• pp.539-551
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• 2005

Finite elements based on isoparametric formulation are known to suffer spurious stiffness properties and corresponding stress oscillations, even when care is taken to ensure that completeness and continuity requirements are enforced. This occurs frequently when the physics of the problem requires multiple strain components to be defined. This kind of error, commonly known as locking, can be circumvented by using reduced integration techniques to evaluate the element stiffness matrices instead of the full integration that is mathematically prescribed. However, the reduced integration technique itself can have a further drawback - rank deficiency, which physically implies that spurious energy modes (e.g., hourglass modes) are introduced because of reduced integration. Such instability in an existing stiffness matrix is generally detected by means of an eigenvalue test. In this paper we show that a knowledge of the dimension of the solution space spanned by the column vectors of the strain-displacement matrix can be used to identify the instabilities arising in an element due to reduced/selective integration techniques a priori, without having to complete the element stiffness matrix formulation and then test for zero eigenvalues.

• 품질경영학회지
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• 제49권4호
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• pp.539-550
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• 2021

Purpose: The purpose of this study is to propose a multivariate CUSUM control chart that can detect the out-of-control state fast while monitoring the cross- and auto- correlated multivariate time series data. Methods: We first build models to estimate the observation data and calculate the corresponding residuals. After then, a multivariate CUSUM chart is applied to monitor the residuals instead of the original raw observation data. Vector Autoregression and Artificial Neural Net are selected for the modelling, and Separated-MCUSUM chart is selected for the monitoring. The suggested methods are tested under a number of experimental settings and the performances are compared with those of other existing methods. Results: We find that Artificial Neural Net is more appropriate than Vector Autoregression for the modelling and show the combination of Separated-MCUSUM with Artificial Neural Net outperforms the other alternatives considered in this paper. Conclusion: The suggested chart has many advantages. It can monitor the complicated multivariate data with cross- and auto- correlation, and detects the out-of-control state fast. Unlike other CUSUM charts finding their control limits by trial and error simulation, the suggested chart saves lots of time and effort by approximating its control limit mathematically. We expect that the suggested chart performs not only effectively but also efficiently for monitoring the process with complicated correlations and frequently-changed parameters.

• International journal of advanced smart convergence
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• 제4권1호
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• pp.45-53
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• 2015

This paper is proposed mathematical load modelling based on system identification approach of energy consumption of residential air conditioning. Due to air conditioning is one of the significant equipment which consumes high energy and cause the peak load of power system especially in the summer time. The demand response is one of the solutions to decrease the load consumption and cutting peak load to avoid the reservation of power supply from power plant. In order to operate this solution, mathematical modelling of air conditioning which explains the behaviour is essential tool. The four type of linear model is selected for explanation the behaviour of this system. In order to obtain model, the experimental setup are performed by collecting input and output data every minute of 9,385 BTU/h air-conditioning split type with $25^{\circ}C$ thermostat setting of one sample house. The input data are composed of solar radiation ($W/m^2$) and ambient temperature ($^{\circ}C$). The output data are power and energy consumption of air conditioning. Both data are divided into two groups follow as training data and validation data for getting the exact model. The model is also verified with the other similar type of air condition by feed solar radiation and ambient temperature input data and compare the output energy consumption data. The best model in term of accuracy and model order is output error model with 70.78% accuracy and $17^{th}$ order. The model order reduction technique is used to reduce order of model to seven order for less complexity, then Kalman filtering technique is applied for remove white Gaussian noise for improve accuracy of model to be 72.66%. The obtained model can be also used for electrical load forecasting and designs the optimal size of renewable energy such photovoltaic system for supply the air conditioning.

• 한국산학기술학회논문지
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• 제18권3호
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• pp.718-723
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• 2017

구조설계 실무 현장에서의 구조해석 모델링 방법을 조사해 보면, 대부분의 경우, 삼차원 구조해석을 위해 슬래브를 판요소를 이용한 메쉬의 형태로 모형화 하고, 전단벽을 쉘요소 또는 벽요소를 사용하여 모형화 하고 있다. 여기서 주목할 점은 해석모형 작성의 편의성을 위하여 전단벽을 층과 층 및 기둥선과 기둥선 사이에 존재하는 한 개의 요소로 모형화 한다는 것이다. 이와 같은 모형화 방법은 사용되는 컴퓨터 프로그램에 따라 해석 오류를 발생시킬 수 있으며, 이러한 오류는 해석 결과의 신뢰성을 저하시키게 된다. 따라서 구조해석의 신뢰성을 확보하기 위해서는 이러한 오류가 발생하는 원인을 조사하고 합리적인 모형화 방법을 찾기 위한 연구가 필요하다. 원인 분석을 위한 비교 대상 해석 프로그램은 MIDAS와 SAP2000 및 neoMAX등과 같은 상용프로그램과 요소의 강성을 추측하기 위해 연구용인 sNs를 사용하였다. 본 연구에서는, 구조해석 실무현장에서 사용하고 있는 전단벽 모형화 방법에 따른 해석오류의 원인들을 분석해 보고자 한다. 또한 이러한 분석 결과를 바탕으로 전단벽 모형화를 위한 몇 가지 고려사항들을 제시하고자 한다.

• Journal of Forest and Environmental Science
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• 제32권3호
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• pp.280-290
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• 2016

Stem diameter variability is an essential inventory result that provides useful information in forest management decisions. Little has been done to explore the modelling potentials of standard deviation (SDD) and coefficient of variation (CVD) of diameter at breast height (dbh). This study, therefore, was aimed at developing and testing models for predicting SDD and CVD in stands of Pinus caribaea Morelet (pine) in south west Nigeria. Sixty temporary sample plots of size $20m{\times}20m$, ranging between 15 and 37 years were sampled, covering the entire range of pine in south west Nigeria. The dbh (cm), total and merchantable heights (m), number of stems and age of trees were measured within each plot. Basal area ($m^2$), site index (m), relative spacing and percentile positions of dbh at $24^{th}$, $63^{rd}$, $76^{th}$ and $93^{rd}$ (i.e. $P_{24}$, $P_{63}$, $P_{76}$ and $P_{93}$) were computed from measured variables for each plot. Linear mixed model (LMM) was used to test the effects of locations (fixed) and plots (random). Six candidate models (3 for SDD and 3 for CVD), using three categories of explanatory variables (i.e. (i) only stand size measures, (ii) distribution measures, and (iii) combination of i and ii). The best model was chosen based on smaller relative standard error (RSE), prediction residual sum of squares (PRESS), corrected Akaike Information Criterion ($AIC_c$) and larger coefficient of determination ($R^2$). The results of the LMM indicated that location and plot effects were not significant. The CVD and SDD models having only measures of percentiles (i.e. $P_{24}$ and $P_{93}$) as predictors produced better predictions than others. However, CVD model produced the overall best predictions, because of the lower RSE and stability in measuring variability across different stand developments. The results demonstrate the potentials of CVD in modelling stem diameter variability in relationship with percentiles variables.

• 한국토양비료학회지
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• 제50권2호
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• pp.115-126
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• 2017

There is an increasing concern over arsenic (As) contamination in rice. This study was conducted to develope a prediction model for As uptake by rice based on the physico-chemical properties of soil. Soil and brown rice samples were collected from 46 sites in paddy fields near three different areas of closed mines and industrial complexes. Total As concentration, soil pH, Al oxide, available phosphorus (avail-P), organic matter (OM) content, and clay content in the soil samples were determined. Also, 1.0 N HCl, 1.0 M $NH_4NO_3$, 0.01 M $Ca(NO_3)_2$, and Mehlich 3 extractable-As in the soils were measured as phytoavailable As concentration in soil. Total As concentration in brown rice samples was also determined. Relationships among As concentrations in brown rice, total As concentrations in soils, and selected soil properties were as follows: As concentration in brown rice was negatively correlated with soil pH value, where as it was positively correlated with Al oxide concentration, avail-P concentration, and OM content in soil. In addition, the concentration of As in brown rice was statistically correlated only with 1.0 N HCl-extractable As in soil. Also, using multiple stepwise regression analysis, a modelling equation was created to predict As concentration in brown rice as affected by selected soil properties including soil As concentration. Prediction of As uptake by rice was delineated by the model [As in brown rice = 0.352 + $0.00109^*$ HCl extractable As in soil + $0.00002^*$ Al oxide + $0.0097^*$ OM + $0.00061^*$ avail-P - $0.0332^*$ soil pH] ($R=0.714^{***}$). The concentrations of As in brown rice estimated by the modelling equation were statistically acceptable because normalized mean error (NME) and normalized root mean square error (NRMSE) values were -0.055 and 0.2229, respectively, when compared with measured As concentration in the plant.

• 한국음향학회지
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• 제37권6호
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• pp.412-421
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• 2018

선 배열 소나는 배열 이득으로 인해 단일 소나에 비해 상대적으로 음압이 낮은 표적 신호일 경우에도 방위 추정이 가능한 장점이 있다. 하지만 선 배열 소나에서는 표적의 방향을 나타내는 표적 방위각과 음파의 다중경로에서 발생되는 수직각의 영향으로 방위 오차가 발생하며 이로 인해 수신 신호로부터 표적 방위를 추정하는데 어려움이 존재한다. 수중의 음파 전달 환경에 의해 발생하는 다중경로는 각 경로별로 상이한 수직각을 가지므로 이러한 특성이 선배열 소나의 방위 추정에 미치는 영향에 대해 고려할 필요가 있다. 본 논문에서는 선 배열 소나에서 다중경로의 영향으로 인해 발생하게 되는 방위 오차를 확인하며 해저면 반사 경로에서 수직각에 의한 오차를 모의하여 환경에 따른 방위 오차의 차이를 분석한다. 또한 추정된 방위각에서 거리에 따라 방위 오차를 고려한 예상 표적 방위선을 도출한다.

• 한국산업정보학회논문지
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• 제18권4호
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• pp.61-72
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• 2013

수출증가가 경제성장을 초래한다는 수출주도성장가설에 관한 실증분석은 주로 개발도상국을 대상으로 하여 시계열 또는 횡단면 자료를 이용하여 지난 1970년대 초부터 최근까지 주요한 관심사가 되어 왔다. 이와 같은 수출주도성장가설에 관한 실증분석은 한국을 포함하여 주로 개발도상국가에 해당되는 아시아 국가들을 분석 대상으로 이루어져 왔다. 본 논문은 여러 국가들의 횡단면 분석보다는 한국의 제조산업에 초점을 맞추어 공적분검정과 오차수정모형을 추정하여 산업의 수출증가와 산업의 성장과의 관계를 조명함으로서 수출주도성장 가설을 검정하였다. 생산과 수출에서 비중이 큰 석유화학, 1차 금속 그리고 조립금속 운송기계를 포함하여 8개의 제조산업 중 6개의 제조산업이 양방향의 인과관계성을 보이고 있기 때문에 한국 제조산업에서는 전반적으로 실질수출액과 실질생산액에 사이에서 양방향의 인과성 관계가 존재한다고 결론을 내릴 수 있다.

• Smart Structures and Systems
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• 제33권2호
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• pp.119-131
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• 2024

Drift angle is a significant index for diagnosing post-event structures. A common way to estimate this drift response is by using modal parameters identified under natural excitations. Although the modal parameters of shear structures cannot be identified accurately in the real environment, the identification error has little impact on the estimation when measurements from several floors are used. However, the estimation accuracy falls dramatically when there is only one accelerometer. This paper describes the susceptibility of single sensor identification to modelling error and simulations that preliminarily verified this characteristic. To make a robust evaluation from measurements of one floor of shear structures based on imprecisely identified parameters, a novel scheme is devised to approximately correct the mode shapes with respect to fictitious frequencies generated with a genetic algorithm; in particular, the scheme uses constrained minimization to take both the mathematical aspect and the realistic aspect of the mode shapes into account. The algorithm was validated by using a full-scale shear building. The differences between single-sensor and multiple-sensor estimations were analyzed. It was found that, as the number of accelerometers decreases, the error rises due to insufficient data and becomes very high when there is only one sensor. Moreover, when measurements for only one floor are available, the proposed method yields more precise and appropriate mode shapes, leading to a better estimation on the drift angle of the lower floors compared with a method designed for multiple sensors. As well, it is shown that the reduction in space complexity is offset by increasing the computation complexity.